scholarly journals Columnar Aerosol Optical Property Characterization and Aerosol Typing Based on Ground-Based Observations in a Rural Site in the Central Yangtze River Delta Region

2022 ◽  
Vol 14 (2) ◽  
pp. 406
Author(s):  
Yong Xie ◽  
Yi Su ◽  
Xingfa Gu ◽  
Tiexi Chen ◽  
Wen Shao ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Aerosol Optical Depth ◽  
Optical Depth ◽  
Yangtze River ◽  
Yangtze River Delta ◽  
River Delta ◽  
Central China ◽  
Rural Site ◽  
Classification Methods ◽  
Aerosol Classification

Accurate and updated aerosol optical properties (AOPs) are of vital importance to climatology and environment-related studies for assessing the radiative impact of natural and anthropogenic aerosols. We comprehensively studied the columnar AOP observations between January 2019 and July 2020 from a ground-based remote sensing instrument located at a rural site operated by Central China Comprehensive Experimental Sites in the center of the Yangtze River Delta (YRD) region. In order to further study the aerosol type, two threshold-based aerosol classification methods were used to investigate the potential categories of aerosol particles under different aerosol loadings. Based on AOP observation and classification results, the potential relationships between the above-mentioned results and meteorological factors (i.e., humidity) and long-range transportation processes were analyzed. According to the results, obvious variation in aerosol optical depth (AOD) during the daytime, as well as throughout the year, was revealed. Investigation into AOD, single-scattering albedo (SSA), and absorption aerosol optical depth (AAOD) revealed the dominance of fine-mode aerosols with low absorptivity. According to the results of the two aerosol classification methods, the dominant aerosol types were continental (accounting for 43.9%, method A) and non-absorbing aerosols (62.5%, method B). Longer term columnar AOP observations using remote sensing alongside other techniques in the rural areas in East China are still needed for accurate parameterization in the future.

Comparison of GOCI and Himawari-8 aerosol optical depth for deriving full-coverage hourly PM2.5 across the Yangtze River Delta

2019 ◽  
Vol 217 ◽  
pp. 116973 ◽  
Author(s):  
Die Tang ◽  
Dongren Liu ◽  
Yulei Tang ◽  
Barnabas C. Seyler ◽  
Xunfei Deng ◽  
...  
Keyword(s):  
Aerosol Optical Depth ◽  
Optical Depth ◽  
Yangtze River ◽  
Yangtze River Delta ◽  
River Delta ◽  
The Yangtze River ◽  
Full Coverage ◽  
The Yangtze River Delta

Variation in MERRA-2 aerosol optical depth over the Yangtze River Delta from 1980 to 2016

2018 ◽  
Vol 136 (1-2) ◽  
pp. 363-375 ◽  
Author(s):  
Enwei Sun ◽  
Huizheng Che ◽  
Xiaofeng Xu ◽  
Zhenzhu Wang ◽  
Chunsong Lu ◽  
...  
Keyword(s):  
Aerosol Optical Depth ◽  
Optical Depth ◽  
Yangtze River ◽  
Yangtze River Delta ◽  
River Delta ◽  
The Yangtze River ◽  
The Yangtze River Delta

scholarly journals Spatiotemporal Variability and Influencing Factors of Aerosol Optical Depth over the Pan Yangtze River Delta During the 2014–2017 Period

2019 ◽  
Vol 16 (19) ◽  
pp. 3522 ◽  
Author(s):  
Cheng ◽  
Li ◽  
Chen ◽  
Hu ◽  
Yuan ◽  
...  
Keyword(s):  
Linear Regression ◽  
Aerosol Optical Depth ◽  
Influencing Factors ◽  
Optical Depth ◽  
Yangtze River ◽  
Geographical Area ◽  
Yangtze River Delta ◽  
River Delta ◽  
Spatiotemporal Variability ◽  
Spatial Coverage

Large amounts of aerosol particles suspended in the atmosphere pose a serious challenge to the climate and human health. In this study, we produced a dataset through merging the Moderate Resolution Imaging Spectrometers (MODIS) Collection 6.1 3-km resolution Dark Target aerosol optical depth (DT AOD) with the 10-km resolution Deep Blue aerosol optical depth (DB AOD) data by linear regression and made use of it to unravel the spatiotemporal characteristics of aerosols over the Pan Yangtze River Delta (PYRD) region from 2014 to 2017. Then, the geographical detector method and multiple linear regression analysis were employed to investigate the contributions of influencing factors. Results indicate that: (1) compared to the original Terra DT and Aqua DT AOD data, the average daily spatial coverage of the merged AOD data increased by 94% and 132%, respectively; (2) the values of four-year average AOD were high in the north-east and low in the south-west of the PYRD; (3) the annual average AOD showed a decreasing trend from 2014 to 2017 while the seasonal average AOD reached its maximum in spring; and that (4) Digital Elevation Model (DEM) and slope contributed most to the spatial distribution of AOD, followed by precipitation and population density. Our study highlights the spatiotemporal variability of aerosol optical depth and the contributions of different factors over this large geographical area in the four-year period, and can, therefore, provide useful insights into the air pollution control for decision makers.

Retrieval of aerosol optical depth over the Yangtze River Delta with HJ-1 data

2014 ◽  
Author(s):  
Lu Zhang ◽  
Runhe Shi ◽  
Yongming Xu ◽  
Long Li ◽  
Wei Gao
Keyword(s):  
Aerosol Optical Depth ◽  
Optical Depth ◽  
Yangtze River ◽  
Yangtze River Delta ◽  
River Delta ◽  
The Yangtze River ◽  
The Yangtze River Delta

Validation of MODIS derived aerosol optical depth over the Yangtze River Delta in China

2010 ◽  
Vol 114 (8) ◽  
pp. 1649-1661 ◽  
Author(s):  
Qianshan He ◽  
Chengcai Li ◽  
Xu Tang ◽  
Huiling Li ◽  
Fuhai Geng ◽  
...  
Keyword(s):  
Aerosol Optical Depth ◽  
Optical Depth ◽  
Yangtze River ◽  
Yangtze River Delta ◽  
River Delta ◽  
The Yangtze River ◽  
The Yangtze River Delta

scholarly journals Anthropogenic CH4 Emissions in the Yangtze River Delta Based on A “Top-Down” Method

Atmosphere ◽  
2019 ◽  
Vol 10 (4) ◽  
pp. 185 ◽  
Author(s):  
Wenjing Huang ◽  
Wei Xiao ◽  
Mi Zhang ◽  
Wei Wang ◽  
Jingzheng Xu ◽  
...  
Keyword(s):  
Yangtze River ◽  
Co2 Concentration ◽  
Yangtze River Delta ◽  
River Delta ◽  
Rural Site ◽  
Ch4 Emission ◽  
The Yangtze River ◽  
Top Down ◽  
Ch4 Emissions ◽  
The Yangtze River Delta

There remains significant uncertainty in the estimation of anthropogenic CH4 emissions at local and regional scales. We used atmospheric CH4 and CO2 concentration data to constrain the anthropogenic CH4 emission in the Yangtze River Delta one of the most populated and economically important regions in China. The observation of atmospheric CH4 and CO2 concentration was carried out from May 2012 to April 2017 at a rural site. A tracer correlation method was used to estimate the anthropogenic CH4 emission in this region, and compared this “top-down” estimate with that obtained with the IPCC inventory method. The annual growth rates of the atmospheric CO2 and CH4 mole fractions are 2.5 ± 0.7 ppm year−1 and 9.5 ± 4.7 ppb year−1, respectively, which are 9% and 53% higher than the values obtained at Waliguan (WLG) station. The average annual anthropogenic CH4 emission is 4.37 (± 0.61) × 109 kg in the YRD (excluding rice cultivation). This “top-down” estimate is 20–70% greater than the estimate based on the IPCC method. We suggest that possible sources for the discrepancy include low biases in the IPCC calculation of emission from landfills, ruminants and the transport sector.

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